Datasets:

mrinaldi
/

TestiMole

@@ -311,10 +311,10 @@ configs:
     path: wikimedia_others/train-*
 ---
 WARNING: THIS "README" IS JUST A STUB, IT WILL BE IMPROVED DURING THE
-NEXT FEW DAYS, GRAMMATICALLY CHECKED AND FILLED WITH MANY OTHER
 INFORMATIONS AND DETAILED STATISTICS
-**Testimole** -- A multi-billion Italian text corpus
 The goal of this work is to create a huge linguistic resource for the
 Italian language that can be used for several NLP applications,
@@ -343,9 +343,9 @@ cl100k\_base model \[2\] was used for tokenization. This dataset is
 composed of several sub-datasets, each with different types of data and
 goals.
-Conversational (\~ 85 Billions tokens):
-UsenetArchiveIT
 This is the project that started the entire work: the goal was to
 collect the largest possible amount of Usenet posts published in the
@@ -378,7 +378,7 @@ here are general stats about this part of the dataset:
 83GB of JSONL file before the conversion to HuggingFace dataset
-Forum
 The second part of the project is the one that produced the largest
 amount of data. 62.415.825.978 A list of Italian message boards based on
@@ -418,7 +418,7 @@ Regarding multimodality, in short: this feature is not very well
 implemented. More details will follow, but do not expect too much
 regarding this point.
-General notes on conversational datasets:
 The data contained in the "usenet" and "forums" splits were generated by
 Italian users of the Internet between 1995 and 2024. For this reason,
@@ -455,7 +455,9 @@ The post should not contain personal information as in all the forums
 internal rules was asked to the user not to share personal information
 as they would have been publicly available on the web.
-OJS
 This split of the dataset contains articles published as Open Access
 using the platform OJS. It comprised mainly academic journals from
@@ -464,7 +466,7 @@ dataset. All the articles are published with Creative Commons licenses,
 and the license used for the single article can be retrieved from the
 metadata.
-Blogs
 This resource was gathered by scraping data from blogs written in
 Italian. The project started with a collection of blogs regarding
@@ -508,7 +510,7 @@ annotated so it could be used for interesting diachronic analysis.
 Finally, the blog split contains also an annotation for the language
 used, as identified by the FastText library.
-Wikimedia
 This split doesn't need many explanation as it is simply a dump of
 wikimedia resources in Italian (Wikipedia, Wikibooks, Wikinews,
@@ -527,7 +529,7 @@ included in this split are: eml (emilian e rumagno) ,fur (furlan) ,la
 (sicilianu) ,sc (sardu) and vec (veneto). Using this data, depending
 from the goal of the project, could produce very interesting results.
-Books
 This collection contains mainly the books coming from LiberLiber's
 project "Manuzio" \[2\]. The books were downloaded from the website in
@@ -541,7 +543,7 @@ sources, such as the Creative Commons licensed school books of
 "Matematicamente" \[3\] and Oilproject-Weschool \[4\] as well as some
 other CC and PD license book found online.
-Websites
 I created a very generic script that is able to extract all the text of
 a website as well as the text contained in Office, PDF and TeX
@@ -561,12 +563,15 @@ that we will discuss in the appropriate section.
 Despite these two point, users are encouraged to use this section as it
 is composed of medium-high and high quality contents.
-Reddit
 It contains a small subsets (4192672 messages) of conversations in some
 Italian subreddits.
-DEDUPLICATION
 The presence of duplicate text can be, depending from the use cases, a
 big problem for several machine learning tasks. I tried to avoid as much
@@ -611,7 +616,13 @@ in the form of 1) header of the website 2) list of links 3) footer of
 the website. All the HTML was converted using HTML2TEXT so it should not
 contain html code.
-References
 \* \[1\] <https://pdai.info/>

     path: wikimedia_others/train-*
 ---
 WARNING: THIS "README" IS JUST A STUB, IT WILL BE IMPROVED DURING THE
+NEXT FEW DAYS AND FILLED WITH MANY OTHER
 INFORMATIONS AND DETAILED STATISTICS
+**Testimole -- A multi-billion Italian text corpus **
 The goal of this work is to create a huge linguistic resource for the
 Italian language that can be used for several NLP applications,
 composed of several sub-datasets, each with different types of data and
 goals.
+**Conversational (\~ 85 Billions tokens):**
+**UsenetArchiveIT**
 This is the project that started the entire work: the goal was to
 collect the largest possible amount of Usenet posts published in the
 83GB of JSONL file before the conversion to HuggingFace dataset
+**Forum**
 The second part of the project is the one that produced the largest
 amount of data. 62.415.825.978 A list of Italian message boards based on
 implemented. More details will follow, but do not expect too much
 regarding this point.
+**General notes on conversational datasets:**
 The data contained in the "usenet" and "forums" splits were generated by
 Italian users of the Internet between 1995 and 2024. For this reason,
 internal rules was asked to the user not to share personal information
 as they would have been publicly available on the web.
+**General**
+**OJS**
 This split of the dataset contains articles published as Open Access
 using the platform OJS. It comprised mainly academic journals from
 and the license used for the single article can be retrieved from the
 metadata.
+**Blogs**
 This resource was gathered by scraping data from blogs written in
 Italian. The project started with a collection of blogs regarding
 Finally, the blog split contains also an annotation for the language
 used, as identified by the FastText library.
+**Wikimedia**
 This split doesn't need many explanation as it is simply a dump of
 wikimedia resources in Italian (Wikipedia, Wikibooks, Wikinews,
 (sicilianu) ,sc (sardu) and vec (veneto). Using this data, depending
 from the goal of the project, could produce very interesting results.
+**Books**
 This collection contains mainly the books coming from LiberLiber's
 project "Manuzio" \[2\]. The books were downloaded from the website in
 "Matematicamente" \[3\] and Oilproject-Weschool \[4\] as well as some
 other CC and PD license book found online.
+**Websites**
 I created a very generic script that is able to extract all the text of
 a website as well as the text contained in Office, PDF and TeX
 Despite these two point, users are encouraged to use this section as it
 is composed of medium-high and high quality contents.
+**Reddit**
 It contains a small subsets (4192672 messages) of conversations in some
 Italian subreddits.
+**Italatex**
+Still work in progress. A collection of materials written in LaTeX.
+**DEDUPLICATION**
 The presence of duplicate text can be, depending from the use cases, a
 big problem for several machine learning tasks. I tried to avoid as much
 the website. All the HTML was converted using HTML2TEXT so it should not
 contain html code.
+**Detailed statistics**
+*Work in progress; this will contain statistics of tokens, chars and sentences lenght for each diachronic resource (usenet newsgroup, post, blog) for each month for each year*
+**Conclusions**
+**References (partial)**
 \* \[1\] <https://pdai.info/>